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Eurofins

Global lab testing and analytics network

Senior Scientific Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeStafford, TX, USAIn-person

About the Job

Requirements

  • A bachelor's or master's degree in Computer Science, Data Engineering, or a related technical field, or equivalent practical experience.
  • Expert-level proficiency in Python, including packages such as Pandas and NumPy, and familiarity with data engineering libraries.
  • Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP), preferably Azure, including computing, storage, and serverless-function services such as Azure Data Lake Storage, Azure Compute virtual machines, or Azure Functions.
  • Experience building and managing data workflows with an orchestration tool such as Apache Airflow, Prefect, or Dagster.
  • Strong knowledge of SQL and experience with relational and NoSQL databases, including PostgreSQL.
  • Proficiency with Git and standard DevOps practices.
  • Prior experience handling and processing complex, large-volume scientific data, such as mass spectrometry, chromatography, or LIMS/ELN integration.
  • Familiarity with MLOps platforms and tools such as Azure ML Studio, MLflow, Kubeflow, or SageMaker.
  • Basic understanding of analytical chemistry concepts, including chromatography fundamentals such as retention time and peak integration, and relevant file formats.
  • Authorization to work in the United States without restriction or sponsorship.
  • Professional working proficiency in English, including the ability to read, write, and speak English.
  • Strong analytical and problem-solving skills focused on delivering high-quality, reproducible data solutions.
  • Verbal and written communication skills sufficient to bridge technical infrastructure, data science models, and chemical applications.

Responsibilities

  • Design, construct, and manage scalable, reliable ETL/ELT pipelines to ingest, clean, transform, and store raw chemistry data, including CSV, JSON, and proprietary instrument formats.
  • Develop optimized data models and manage a data warehouse or data lake to support fast querying and machine-learning feature engineering on complex datasets, including time-series and chromatogram spectral data.
  • Collaborate with Machine Learning Engineers to containerize and deploy machine-learning models and build automated model retraining and monitoring pipelines.
  • Implement data quality checks, validation, and monitoring to ensure the integrity and reproducibility of chemical experiment data used for machine learning.
  • Develop internal tools and APIs to facilitate data access for Machine Learning Engineers and provide standardized interfaces for data submission from chemistry lab systems.

About the Company

Eurofins

Global lab testing and analytics network

Eurofins provides global laboratory testing and analytical services to verify the safety, authenticity, and quality of products across food, water, medicine, and the environment. It operates a network of more than 900 laboratories in over 60 countries, offering access to more than 200,000 analytical methods. Its product work involves running specialized tests—using chemistry, biology, and other scientific techniques—to confirm origin, composition, and compliance of samples, such as detecting wine fraud or contaminant presence. The company differentiates itself through its massive, distributed lab network and broad portfolio, enabling standardized testing at scale and fast turnaround across many industries, rather than relying on a single specialty or location. Its goal is to protect public health and safety by delivering accurate, comprehensive testing data and helping clients meet regulatory and quality requirements.

Company size
10,001+
Company stage
IPO
Headquarters
Luxembourg
Founded
1987

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